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Shuttle Topography Data Inform Solar Power Analysis

Sunday, 01 January 2012

NASA Technology

The next time you flip on a light switch, there’s a
chance that you could be benefitting from data
originally acquired during the Space Shuttle
Program. An effort spearheaded by Jet Propulsion
Laboratory (JPL) and the National Geospatial-Intelligence
Agency (NGA) in 2000 put together the first near-global
elevation map of the Earth ever assembled, which has
found use in everything from 3D terrain maps to models
that inform solar power production.

For the project, called the Shuttle Radar Topography
Mission (SRTM), engineers at JPL designed a 60-meter
mast that was fitted onto Shuttle Endeavour. Once
deployed in space, an antenna attached to the end of the
mast worked in combination with another antenna on the
shuttle to simultaneously collect data from two perspectives.
Just as having two eyes makes depth perception
possible, the SRTM data sets could be combined to form
an accurate picture of the Earth’s surface elevations—
the first hight-detail, near-global elevation map ever
assembled.

What made SRTM unique was not just its surface
mapping capabilities but the completeness of the data
it acquired. Over the course of 11 days, the shuttle
orbited the Earth nearly 180 times, covering everything
between the 60° north and 54° south latitudes, or roughly
80 percent of the world’s total landmass. Of that targeted
land area, 95 percent was mapped at least twice, and
24 percent was mapped at least four times.

Following several years of processing, NASA released
the data to the public in partnership with NGA. Robert
Crippen, a member of the SRTM science team, says that
the data have proven useful in a variety of fields. “Satellites
have produced vast amounts of remote sensing data, which
over the years have been mostly two-dimensional. But the
Earth’s surface is three-dimensional. Detailed topographic
data give us the means to visualize and analyze remote
sensing data in their natural three-dimensional structure,
facilitating a greater understanding of the features and
processes taking place on Earth.”

Technology Transfer

Seeing the potential for elevation data to play a role in
solar power modeling and planning, the California Public
Utilities Commission asked Jan Kleissl, a professor of
environmental engineering at the University of California
San Diego, to use the SRTM data to build models showing
how much shade an area on the ground receives given
its horizon—that is, to what degree nearby terrain (such
as a large hill) blocks out the sun during the day.

By identifying places prone to long periods either with
or without direct sunlight, Kleissl’s data can assist people
who are planning to build solar installations. “What we
did was take the data and post-process it, analyzing the
elevations to simulate what the horizon would be for any
place on the map,” says Kleissl. Horizon modeling proved
a resource-consuming task, he says. “It’s a different metric
than elevation, because you have to relate a given point to
all of its surroundings.”

But with the modeling done, multiple parties expressed
interest in the resulting product. “We weren’t the first
ones to do this analysis,” says Kleissl, “but we were the
first ones to do it on a large spatial area. We’ve covered
the whole of Southern California and parts of the Bay
Area. All of that is now a publicly available data set that
we provide to anyone who is interested.”

Among the companies who acquired Kleissl’s data was
New York City-based Locus Energy LLC. Locus Energy
provides technology for analyzing and monitoring distributed
solar installations; it offers historical, real-time, and
forecasting information that helps power providers plan
for and predict solar power production. The company
draws the bulk of its data—mostly cloud formation and
movement—using NASA’s geostationary operational
environmental satellite system (GOES), or the weather
satellites designed by NASA and operated by the National
Oceanic and Atmospheric Administration.

Along with the data provided by GOES, the SRTM
data that has been processed by Kleissl helps Locus
Energy accurately determine how much solar energy is
reaching a given location. Says Shawn Kerrigan, CTO of
Locus Energy, “We combine these two data sets to model
how much solar irradiance is hitting a particular location.
The understanding that we’re developing with the help
of NASA data, integrated with some of the knowledge
and expertise we have, gives us some interesting insights
into how much power is produced at distributed solar
installations.”

Benefits

Locus Energy’s NASA-derived services have been
incorporated into its Virtual Irradiance project—a software
package that can estimate solar irradiance without
the need for a physical sensor. “We deal with a lot of
small- to mid-sized solar installations in distributed solar
space,” says Kerrigan. “In order to understand how well
their equipment is performing, these companies would
otherwise have to install a sensor at each site. But it’s
often prohibitively expensive to do so.”

As Kerrigan likes to say, Locus Energy “replaces
expensive hardware with smarter software,” potentially
bringing down the cost of solar energy as a whole.
The savings offered merely by replacing those sensors
with software is significant: Kerrigan says that a typical
sensor might cost about $1,000 on average. “Our fleet
consists of more than 130,000 monitored nodes, each
of which would require
its own sensor to acquire
the information we can
provide,” he says. Those
savings only reflect the initial cost
of purchasing sensors; companies stand to save even more
in ongoing operation and maintenance costs.

According to the company, each set of data—
historical, real-time, and forecasting—has a different
value proposition. The historical data provides a basis
for “solar prospecting,” or the process of determining
which location would be most effective for deploying a
solar system. Virtual Irradiance’s forecasting models use
current cloud formation to develop a forward-looking
picture of what cloud cover will be like to develop an
accurate estimate of solar resource availability for the near
future.

Kerrigan credits NASA’s SRTM and GOES data as
an essential piece of what Locus Energy offers. “It’s fundamental
to the modeling we’re doing. Without it, we
literally would not be able to do our forecasting work,” he
says. “And the same thing applies to the real-time and historical
data we do. Without NASA data, we would have
to rely on other weather models that are less effective.
NASA’s technology is at the core of our technology.”

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